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Semiconductor Manufacturing
Transforming edge computing through intelligent human interface solutions.
In this episode, we talk about how TUM researchers are trying to model the effects of climate change on forest fires using a neural network, why robots assisting with getting dressed is more challenging than it seems, how drones are being used to evacuate elderly in nursing homes during emergencies.
2 minutes read
Theory-based residual neural network combines discrete choice models and deep neural networks, long viewed as conflicting methods.
In this episode, we talk about how DeepMind’s AlphaFold algorithm solved protein folding, NASA JPL’s partnership with the Department of Homeland Security to better protect firefighters, and a trial for autonomous shuttles in DTU that can change the transportation infrastructure of the whole country
Deep learning algorithms reveal the rules of gene regulation
Duke team disentangles neural networks to understand how they see the world
A new approach to image search uses images returned by traditional search methods as nodes in a graph neural network through which similarity signals are propagated, achieving improved ranking in cross-modal retrieval.
14 minutes read
Article 7 of our Cobot Series: Cobots have already staked their ground as a “must have” for industrial automation, but they’ve really just scratched the surface of what they can achieve.
By building the enormous network of wireless sensors that forms the IoT, we’re generating more data than ever before. More data promises better decision making – but only if we don’t drown in information first.
3 minutes read
Ultra-low-power MCU’s and highly efficient purpose-built chips are bringing voice to the edge.
In recent years, we have experienced the success of modern machine learning (ML) models. Many of them have led to unprecedented breakthroughs in a wide range of applications, such as AlphaGo beating a world champion human player or the introduction of autonomous vehicles.
